Permanent surface and downhole sensor technology is increasingly being implemented to enable real time monitoring and reservoir management. Acquiring vast quantities of data in real time at high frequencies is useful only if data processing and interpretation can be done at same time scales. Otherwise the value of high frequency information is lost. U.S. patent application Ser. No. 09/705,674 to Ramakrishnan et al. (the '674 Application) now an issued U.S. Pat. No. 7,096,092 (incorporated herein by reference in its entirety) teaches methods for real time data acquisition and remote reservoir management using information from permanent sensors. U.S. patent application Ser. No. 10/442,216 (or US Publication Application Number 2004/0010374, pending) to Raghuraman et al. (the '216 Application) (incorporated herein by reference in its entirety) teaches methods to efficiently process and interpret vast quantities of data acquired from permanent sensors. The '216 Application outlines algorithms for processing data at relevant time scales. The subsequent interpretation is then done using increasingly detailed levels of modeling so that the levels of modeling match the time scale of data processing. For example a pressure-pressure derivative correlation across two locations in a reservoir may be done to estimate the pressure diffusion time between these two locations and used as a tracker for formation properties (permeability, fluid mobility, porosity) over time (see the '674 Application, and Raghuraman, et al., “Interference Analysis of Cemented-Permanent-Sensor Data from a Field Experiment,” (M019), Jun. 11-15, 2001, EAGE 63rd Conference & Technical Exhibition, Amsterdam, incorporated herein by reference in its entirety). This is a quick look interpretation that can easily be done over a time scale of hours/days as opposed to a full-scale reservoir simulation that takes a time scale of weeks/months. Such quick look interpretation methods, which match time scales of data collection, are needed if one has to maximize the value of high frequency information from permanent sensors. They can be useful for tracking changes in formation properties over time as well as for constraining more detailed reservoir models.
In principle, well-testing constitutes an inverse problem. One starts with assumptions regarding the reservoir, and based on the transient response attempts to estimate the relevant properties. System identification techniques through deconvolution, type-curve matching for the reservoir model, and variants of Newton iterative techniques are common in well-test interpretation. Conventional well testing implies a production or an injection test, and monitoring the resulting pressure behavior at the wellbore. (See Earlugher, “Advances in Well Test Analysis,” Soc. Pet. Eng. AIME, New York (1977); Matthews et al., “Pressure Buildup and Flow Tests in Wells,” Soc. Pet. Eng. AIME, New York (1967); and Raghavan, Well Test Analysis, Prentice Hall (1993), incorporated by reference herein in their entireties). Adequate shut-in prior to a well test, or alternatively, inclusion of rate data, is important in order to eliminate the influence of historical production in the interpretation. Significant emphasis is placed on the determination of skin-factor in such tests. In contrast, in interference testing, pressure is measured in a shut-in well, termed the observation well. Other wells continue to be active. Such tests can be useful in estimating reservoir scale permeabilities between the observer and the other wells, if one chooses to deploy a suitable testing scheme. The physics of the method is substantively the same as conventional testing schemes; but the methodology and the procedures are different.
An enhancement to interference testing is the pulsed interference testing, wherein a periodic pulsing of a well is carried out, and the response at an observation well is analyzed. (See Brigham, “Planning and Analysis of Pulse-Tests,” J. Pet. Technol. (1970), volume 22, pages 618-624; Johnson et al., “Pulse-testing: A new method for describing reservoir flow properties between wells,” J. Pet. Technol. (1966), volume 18, pages 1599-1604; Kamal et al., “Pulse-testing response for unequal pulse and shut-in periods,” J. Pet. Technol. (1975) volume 27, pages 399-410, incorporated by reference herein in their entireties). An extensive set of “type-curves” is available to translate the magnitude and the time-lag of the pulse responses at the observation well. The lag is the time between the beginning of the source pulse and the peak in the pressure response. While such a method was an advance over conventional techniques for estimating inter-well permeability, a certain degree of regularity and ideality for the pulses is required. Calculations are based on extensive table/type-curve look-up, and the applicability of these techniques assume ideal conditions (e.g. periodicity, uniformity etc.). A translation of these methods for continuous updating of interwell permeability with nonsystematic or irregular pulsing is difficult.
Accordingly, the present invention provides a quick look interpretation methodology for cross-correlation of sensor data. Such techniques may be applied to cross-correlation of data from different sensor types at same or different locations.